Define observability in Fabric and give examples of telemetry you would collect.

• A. Observability means monitoring data pipelines and lakehouse performance; collect metrics like job duration, records processed, error rates, latency, and lineage changes.
• B. Observability is only about system uptime.
• C. Telemetry is not collected in Fabric.
• D. Observability focuses only on user access logs.

Answer: (A)

Observability in Fabric is about understanding how the data platform behaves by collecting signals from pipelines, lakehouses, and workloads so you can monitor, troubleshoot, and optimize performance and data quality. The best description highlights monitoring data pipelines and lakehouse performance and gathering telemetry such as job duration, records processed, error rates, latency, and lineage changes. These signals give you a complete view: how long jobs take and how fast results arrive reflect performance and latency; how many records flow through indicates throughput; error rates show reliability; and lineage changes reveal how data moves and transforms, which is vital for trust and impact analysis. In practice, this combination lets you detect issues, pinpoint root causes, and ensure data quality across the platform. Choices that focus only on uptime or claim telemetry isn’t collected, or that emphasize only user access logs, miss the broader set of signals necessary for understanding data workflows and their health.